2.2.2. MLPNN

Multi-layer perceptron neural network is a powerful tool for solving non-linear problems. It consists of an input layer, one or more hidden layers, and an output layer. Each layer contains artificial neurons and the neurons between layers are connected with an adaptable weight. The output of each neuron in each layer is multiplied by the adaptable weight and after passing through a transfer function becomes the input to the next-level neurons. In this research, tuning the weights, which is called the learning process, is realized by a backpropagation algorithm, namely the Levenberg-Marquardt algorithm. The structure of an MLPNN is shown in Figure 5.

**Figure 5.** The structure of the MLPNN.
